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TSsmoothing (version 0.1.0)

Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

Description

It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. --- Guerrero, V.M (2007) . Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) .

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Version

Install

install.packages('TSsmoothing')

Monthly Downloads

143

Version

0.1.0

License

GPL-3

Maintainer

L. Leticia Ramirez-Ramirez

Last Published

July 15th, 2019

Functions in TSsmoothing (0.1.0)

trend_estimate

Trend estimation with controlled smoothing.
trade

Annual Trade for USA and Mexico
preliminar

Preliminar smoothing
positive_definite

Checks if a squared matrix is positive definite and turn it to positive definied if necessary
lambda_value

Calculation of the lambda value.
psigma_estimates

Preliminar estimates
ltable

Lambda values table.
emp_agr

Employment in agriculture
corrmvc

Correlation from a 2d covariance matrix.
plot_trend

Plot fo the time series and its smoothed version in ggplo
sigma_zf

Empirical cross-covarinace.
graph_trend

Plot of original and smoothed time series.
smoothing_level

Smoothing value